def freesurfer_annot_to_vtks(surface_file, label_file, output_stem='',
json_file='files_to_load.json',
sample_rate=1,
force=False, verbose=True, output_dir=DATA_DIR):
""" Splits a surface file into vtk files based on regions in the label file.
"""
def print_verbose(*args):
"""Print only if verbose True"""
if verbose:
print(args)
#
vtk_dir = os.path.join(output_dir, os.path.dirname(output_stem))
# Make the output directory
if not os.path.exists(output_dir):
os.makedirs(vtk_dir)
# Convert the surface file to vtk
if os.path.splitext(surface_file)[1] == '.vtk':
surface_vtk = surface_file
else:
surface_vtk = os.path.join(vtk_dir,
os.path.basename(surface_file) + '.vtk')
if force or not os.path.exists(surface_vtk):
print_verbose('Converting surface to vtk: %s' % surface_file)
from mindboggle.mio.vtks import freesurfer_surface_to_vtk
freesurfer_surface_to_vtk(surface_file, surface_vtk)
# Convert the data file to vtk
if os.path.splitext(label_file)[1] == '.vtk':
label_vtk = label_file
labels, names = None, None
else:
label_vtk = os.path.join(vtk_dir,
os.path.basename(label_file) + '.vtk')
if force or not os.path.exists(label_vtk):
print_verbose('Converting data to vtk: %s' % label_file)
from mindboggle.mio.vtks import freesurfer_annot_to_vtk
freesurfer_annot_to_vtk(label_file, surface_vtk, label_vtk)
labels, _, names = nib.freesurfer.read_annot(label_file)
used_labels = np.unique(labels[labels >= 1])
used_names = np.asarray(names)[used_labels]
print_verbose("Unused areas: %s" % (set(names) - set(used_names)))
names = used_names
labels = used_labels
# Expand the data file to multiple vtks
print_verbose('Expanding vtk data to multiple files.')
from mindboggle.mio.vtks import explode_scalars
explode_output_stem = os.path.join(output_dir, output_stem)
explode_scalars(label_vtk, output_stem=explode_output_stem)
output_vtks = filter(lambda p: p not in [surface_vtk, label_vtk],
glob.glob(explode_output_stem + '*.vtk'))
print_verbose('Downsampling vtk files.')
for vtk_file in output_vtks:
downsample_vtk(vtk_file, sample_rate=sample_rate)
if json_file:
print_verbose('Creating download manifest file.')
if labels is None:
names = labels = [os.path.splitext(vtk_file)[0] for vtk_file in output_vtks]
vtk_dict = dict([(name, output_stem + '%s.vtk' % lbl)
for lbl, name in zip(labels, names)])
json_file = os.path.join(output_dir, json_file)
with open(json_file, 'wb') as fp:
json.dump(dict(filename=vtk_dict), fp)
return json_file
from mindboggle.guts.mesh import decimate_file
subj_path = os.environ['SUBJECTS_DIR']
fsavg_path = os.path.join(subj_path, 'fsaverage')
surf_file = os.path.join(fsavg_path, 'surf', 'lh.pial')
label_file = os.path.join(fsavg_path, 'label', 'lh.aparc.annot')
surf_vtk = 'lh_surf.vtk'
label_vtk = 'lh_label.vtk'
# Convert surface and labels to vtk, break into ROIs
print('Generating vtks')
if not os.path.exists(surf_vtk):
freesurfer_surface_to_vtk(surf_file, surf_vtk)
if not os.path.exists(label_vtk):
freesurfer_annot_to_vtk(label_file, surf_vtk, label_vtk)
# Break into ROIs
if True:
# downsample_vtk(label_vtk, sample_rate=sample_rate)
explode_scalars(label_vtk, output_stem='lh_roi_')
roi_dict = dict([(i, roi_vtk) for i, roi_vtk in enumerate(glob.glob('lh_roi_*.vtk'))])
# Downsample
if False:
print('Downsampling vtks')
for roi_vtk in roi_dict.values():
decimate_file(roi_vtk, reduction=0.5, output_vtk=roi_vtk,
save_vtk=True, smooth_steps=100)